LEADER 05751nam 2200913Ia 450 001 9910964166703321 005 20240416170713.0 010 $a9786611217303 010 $a9786613272959 010 $a9781281217301 010 $a1281217301 010 $a9780470253601 010 $a0470253606 010 $a9781283272957 010 $a1283272954 010 $a9781118086148 010 $a1118086147 035 $a(CKB)2670000000122183 035 $a(EBL)331611 035 $a(OCoLC)608622380 035 $a(SSID)ssj0000097858 035 $a(PQKBManifestationID)11127415 035 $a(PQKBTitleCode)TC0000097858 035 $a(PQKBWorkID)10120720 035 $a(PQKB)10926357 035 $a(SSID)ssj0001349179 035 $a(PQKBManifestationID)11758757 035 $a(PQKBTitleCode)TC0001349179 035 $a(PQKBWorkID)11398744 035 $a(PQKB)11255469 035 $a(Au-PeEL)EBL331611 035 $a(CaPaEBR)ebr10225448 035 $a(CaONFJC)MIL121730 035 $a(PPN)151030308 035 $a(MiAaPQ)EBC331611 035 $a(FR-PaCSA)88944650 035 $a(FRCYB88944650)88944650 035 $a(Perlego)2750106 035 $a(EXLCZ)992670000000122183 100 $a20071019d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAdvanced stochastic models, risk assessment, and portfolio optimization $ethe ideal risk, uncertainty, and performance measures /$fby Svetlozar T. Rachev, Stoyan V. Stoyanov, Frank J. Fabozzi 205 $a1st ed. 210 $aHoboken, N.J. $cWiley ;$a[Chichester $cJohn Wiley, distributor]$d2008 215 $a1 online resource (39 p.) 225 1 $aThe Frank J. Fabozzi series 300 $aDescription based upon print version of record. 311 08$a9780470053164 311 08$a047005316X 320 $aIncludes bibliographical references and index. 327 $aAdvanced Stochastic Models, Risk Assessment, and Portfolio Optimization; Contents; Preface; Acknowledgments; About the Authors; Chapter 1 Concepts of Probability; 1.1 INTRODUCTION; 1.2 BASIC CONCEPTS; 1.3 DISCRETE PROBABILITY DISTRIBUTIONS; 1.4 CONTINUOUS PROBABILITY DISTRIBUTIONS; 1.5 STATISTICAL MOMENTS AND QUANTILES; 1.6 JOINT PROBABILITY DISTRIBUTIONS; 1.7 PROBABILISTIC INEQUALITIES; 1.8 SUMMARY; BIBLIOGRAPHY; Chapter 2 Optimization; 2.1 INTRODUCTION; 2.2 UNCONSTRAINED OPTIMIZATION; 2.3 CONSTRAINED OPTIMIZATION; 2.4 SUMMARY; BIBLIOGRAPHY; Chapter 3 Probability Metrics; 3.1 INTRODUCTION 327 $a3.2 MEASURING DISTANCES: THE DISCRETE CASE3.3 PRIMARY, SIMPLE, AND COMPOUND METRICS; 3.4 SUMMARY; 3.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 4 Ideal Probability Metrics; 4.1 INTRODUCTION; 4.2 THE CLASSICAL CENTRAL LIMIT THEOREM; 4.3 THE GENERALIZED CENTRAL LIMIT THEOREM; 4.4 CONSTRUCTION OF IDEAL PROBABILITY METRICS; 4.5 SUMMARY; 4.6 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 5 Choice under Uncertainty; 5.1 INTRODUCTION; 5.2 EXPECTED UTILITY THEORY; 5.3 STOCHASTIC DOMINANCE; 5.4 PROBABILITY METRICS AND STOCHASTIC DOMINANCE; 5.5 SUMMARY; 5.6 TECHNICAL APPENDIX; BIBLIOGRAPHY 327 $aChapter 6 Risk and Uncertainty6.1 INTRODUCTION; 6.2 MEASURES OF DISPERSION; 6.3 PROBABILITY METRICS AND DISPERSION MEASURES; 6.4 MEASURES OF RISK; 6.5 RISK MEASURES AND DISPERSION MEASURES; 6.6 RISK MEASURES AND STOCHASTIC ORDERS; 6.7 SUMMARY; 6.8 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 7 Average Value-at-Risk; 7.1 INTRODUCTION; 7.2 AVERAGE VALUE-AT-RISK; 7.3 AVaR ESTIMATION FROM A SAMPLE; 7.4 COMPUTING PORTFOLIO AVaR IN PRACTICE; 7.5 BACKTESTING OF AVaR; 7.6 SPECTRAL RISK MEASURES; 7.7 RISK MEASURES AND PROBABILITY METRICS; 7.8 SUMMARY; 7.9 TECHNICAL APPENDIX; BIBLIOGRAPHY 327 $aChapter 8 Optimal Portfolios8.1 INTRODUCTION; 8.2 MEAN-VARIANCE ANALYSIS; 8.3 MEAN-RISK ANALYSIS; 8.4 SUMMARY; 8.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 9 Benchmark Tracking Problems; 9.1 INTRODUCTION; 9.2 THE TRACKING ERROR PROBLEM; 9.3 RELATION TO PROBABILITY METRICS; 9.4 EXAMPLES OF r.d. METRICS; 9.5 NUMERICAL EXAMPLE; 9.6 SUMMARY; 9.7 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 10 Performance Measures; 10.1 INTRODUCTION; 10.2 REWARD-TO-RISK RATIOS; 10.3 REWARD-TO-VARIABILITY RATIOS; 10.4 SUMMARY; 10.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Index 330 $aThis groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers. 410 0$aFrank J. Fabozzi series. 606 $aStochastic processes 606 $aMathematical optimization 606 $aRisk assessment$xMathematical models 606 $aPortfolio management$xMathematical models 615 0$aStochastic processes. 615 0$aMathematical optimization. 615 0$aRisk assessment$xMathematical models. 615 0$aPortfolio management$xMathematical models. 676 $a332 700 $aRachev$b S. T$g(Svetlozar Todorov)$059738 701 $aStoyanov$b Stoyan V$01654203 701 $aFabozzi$b Frank J$0109596 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910964166703321 996 $aAdvanced stochastic models, risk assessment, and portfolio optimization$94336045 997 $aUNINA